TY - JOUR
T1 - A comprehensive review of 5G NR RF-EMF exposure assessment technologies
T2 - fundamentals, advancements, challenges, niches, and implications
AU - Korkmaz, Erdal
AU - Aerts, Sam
AU - Coesoij, Richard
AU - Bhatt, Chhavi Raj
AU - Velghe, Maarten
AU - Colussi, Loek
AU - Land, Derek
AU - Petroulakis, Nikolaos
AU - Spirito, Marco
AU - Bolte, John
PY - 2024
Y1 - 2024
N2 - This review offers a detailed examination of the current landscape of radio frequency (RF) electromagnetic field (EMF) assessment tools, ranging from spectrum analyzers and broadband field meters to area monitors and custom-built devices. The discussion encompasses both standardized and non-standardized measurement protocols, shedding light on the various methods employed in this domain. Furthermore, the review highlights the prevalent use of mobile apps for characterizing 5G NR radio network data. A growing need for low-cost measurement devices is observed, commonly referred to as “sensors” or “sensor nodes”, that are capable of enduring diverse environmental conditions. These sensors play a crucial role in both microenvironmental surveys and individual exposures, enabling stationary, mobile, and personal exposure assessments based on body-worn sensors, across wider geographical areas. This review revealed a notable need for cost-effective and long-lasting sensors, whether for individual exposure assessments, mobile (vehicle-integrated) measurements, or incorporation into distributed sensor networks. However, there is a lack of comprehensive information on existing custom-developed RF-EMF measurement tools, especially in terms of measuring uncertainty. Additionally, there is a need for real-time, fast-sampling solutions to understand the highly irregular temporal variations EMF distribution in next-generation networks. Given the diversity of tools and methods, a comprehensive comparison is crucial to determine the necessary statistical tools for aggregating the available measurement data.
AB - This review offers a detailed examination of the current landscape of radio frequency (RF) electromagnetic field (EMF) assessment tools, ranging from spectrum analyzers and broadband field meters to area monitors and custom-built devices. The discussion encompasses both standardized and non-standardized measurement protocols, shedding light on the various methods employed in this domain. Furthermore, the review highlights the prevalent use of mobile apps for characterizing 5G NR radio network data. A growing need for low-cost measurement devices is observed, commonly referred to as “sensors” or “sensor nodes”, that are capable of enduring diverse environmental conditions. These sensors play a crucial role in both microenvironmental surveys and individual exposures, enabling stationary, mobile, and personal exposure assessments based on body-worn sensors, across wider geographical areas. This review revealed a notable need for cost-effective and long-lasting sensors, whether for individual exposure assessments, mobile (vehicle-integrated) measurements, or incorporation into distributed sensor networks. However, there is a lack of comprehensive information on existing custom-developed RF-EMF measurement tools, especially in terms of measuring uncertainty. Additionally, there is a need for real-time, fast-sampling solutions to understand the highly irregular temporal variations EMF distribution in next-generation networks. Given the diversity of tools and methods, a comprehensive comparison is crucial to determine the necessary statistical tools for aggregating the available measurement data.
KW - 5G new radio
KW - Exposimeter
KW - Exposure assessment
KW - Measurement equipment
KW - Mobile phone-based tools
KW - Personal exposure
KW - Radiofrequency electromagnetic fields
KW - Sensor
UR - http://www.scopus.com/inward/record.url?scp=85199484786&partnerID=8YFLogxK
U2 - 10.1016/j.envres.2024.119524
DO - 10.1016/j.envres.2024.119524
M3 - Review article
C2 - 38972338
AN - SCOPUS:85199484786
SN - 0013-9351
VL - 260
JO - Environmental Research
JF - Environmental Research
M1 - 119524
ER -